Iteratively get the max of a data frame column, add one and repeat for all rows in r - sql

Question

I need to perform a database operation where I'll be adding new data to an existing table and then assigning the new rows a unique id. I'm asking about this in R so I can get the logic straight before I attempt to rewrite it in sql or pyspark.
Imagine that I've already added the new data to the existing data. Here's a simplified version of what it might look like:
library(tidyverse)
df <- tibble(id = c(1, 2, 3, NA, NA),
descriptions = c("dodgers", "yankees","giants", "orioles", "mets"))
# A tibble: 5 x 2
id descriptions
<dbl> <chr>
1 1 dodgers
2 2 yankees
3 3 giants
4 NA orioles
5 NA mets
What I want is:
# A tibble: 5 x 2
id descriptions
<dbl> <chr>
1 1 dodgers
2 2 yankees
3 3 giants
4 4 orioles
5 5 mets
An I can't use arrange with rowid_to_columns id's be deleted.
To get a unique id for the NA rows while not changing the existing ones, I want to get the max of the id column, add one, replace NA with that value and then move to the next row. My instinct was to do something like this: df %>% mutate(new_id = max(id, na.rm = TRUE) + 1) but that only get's the max plus one, not a new max for each row. I feel like I could do this with a mapping function but what I've tried returns a result identical to the input dataframe:
df %>%
mutate(id = ifelse(is.na(id),
map_dbl(id, ~max(.) + 1, na.rm = FALSE),
id))
# A tibble: 5 x 2
id descriptions
<dbl> <chr>
1 1 dodgers
2 2 yankees
3 3 giants
4 NA orioles
5 NA mets
Thanks in advance--now if someone can help me directly in sql, that's also a plus!

Answer 1

SQL option, using sqldf for demo:
sqldf::sqldf("
with cte as (
select max(id) as maxid from df
)
select cte.maxid + row_number() over () as id, df.descriptions
from df
left join cte where df.id is null
union
select * from df where id is not null")
# id descriptions
# 1 1 dodgers
# 2 2 yankees
# 3 3 giants
# 4 4 orioles
# 5 5 mets

Answer 2

Here is one method where we add the max value with the cumulative sum of logical vector based on the NA values and coalesce with the original column 'id'
library(dplyr)
df <- df %>%
mutate(id = coalesce(id, max(id, na.rm = TRUE) + cumsum(is.na(id))))
-output
df
# A tibble: 5 x 2
id descriptions
<dbl> <chr>
1 1 dodgers
2 2 yankees
3 3 giants
4 4 orioles
5 5 mets